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Hand Detection and Gesture Recognition Using Symmetric Patterns
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-5863-0748
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-3034-6630
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-1400-346X
2016 (English)In: Studies in Computational Intelligence, ISSN 1860-949X, E-ISSN 1860-9503, Vol. 642, p. 365-375Article in journal, Meeting abstract (Other academic) Published
Abstract [en]

Hand detection and gesture recognition is one of the challenging issues in human-robot interaction. In this paper we proposed a novel method to detect human hands and recognize gestures from video stream by utilizing a family of symmetric patterns: log-spiral codes. In this case, several log-family spirals mounted on a hand glove were extracted and utilized for positioning the palm and fingers. The proposed method can be applied in real time and even on a low quality camera stream. The experiments are implemented in different conditions to evaluate the illumination, scale, and rotation invariance of the proposed method. The results show that using the proposed technique we can have a precise and reliable detection and tracking of the hand and fingers with accuracy about 98 %. © Springer International Publishing Switzerland 2016.

Place, publisher, year, edition, pages
Heidelberg: Springer Berlin/Heidelberg, 2016. Vol. 642, p. 365-375
Keywords [en]
Hand Detection, Gesture Recognition, Symmetric Patterns, Log-spiral Codes, Human-Robot Interaction
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-40624DOI: 10.1007/978-3-319-31277-4_32ISI: 000390824900032Scopus ID: 2-s2.0-84966539110OAI: oai:DiVA.org:hh-40624DiVA, id: diva2:1353940
Conference
Swedish Symposium on Image Analysis, SSBA, Uppsala, Sweden, March 14-16, 2016
Funder
Knowledge FoundationAvailable from: 2019-09-24 Created: 2019-09-24 Last updated: 2019-10-11

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Mashad Nemati, HassanFan, Yuantao

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